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Record W2103764534 · doi:10.1136/bmj.e1203

Cardiovascular disease in kidney donors: matched cohort study

2012· article· en· W2103764534 on OpenAlex
Amit X. Garg, Aizhan Meirambayeva, Anjie Huang, J. Kim, G. V. Ramesh Prasad, Greg Knoll, Neil Boudville, Charmaine E. Lok, Phil McFarlane, Martin Karpinski, Leroy Storsley, Scott Klarenbach, Ngan N. Lam, Sonia M. Thomas, Christine Dipchand, Peter P. Reese, Mona D. Doshi, Eric M. Gibney, K. Taub, Ann Young

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueBMJ · 2012
Typearticle
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsUniversity of AlbertaUniversity of ManitobaUniversity of OttawaDalhousie UniversityUniversity of TorontoLondon Health Sciences CentreUniversity of CalgaryInstitute for Clinical Evaluative SciencesWestern University
FundersCanadian Institutes of Health ResearchFondation pour la Recherche MédicaleOntario Ministry of Health and Long-Term CareUniversity of AlbertaAlberta InnovatesInstitute for Clinical Evaluative SciencesUniversity of Ottawa
KeywordsMedicineHazard ratioInterquartile rangeCohortPopulationConfidence intervalInternal medicineRetrospective cohort studyCohort studyProportional hazards modelCause of deathDiseaseSurgeryEnvironmental health

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine whether people who donate a kidney have an increased risk of cardiovascular disease. DESIGN: Retrospective population based matched cohort study. PARTICIPANTS: All people who were carefully selected to become a living kidney donor in the province of Ontario, Canada, between 1992 and 2009. The information in donor charts was manually reviewed and linked to provincial healthcare databases. Matched non-donors were selected from the healthiest segment of the general population. A total of 2028 donors and 20,280 matched non-donors were followed for a median of 6.5 years (maximum 17.7 years). Median age was 43 at the time of donation (interquartile range 34-50) and 50 at the time of follow-up (42-58). MAIN OUTCOME MEASURES: The primary outcome was a composite of time to death or first major cardiovascular event. The secondary outcome was time to first major cardiovascular event censored for death. RESULTS: The risk of the primary outcome of death and major cardiovascular events was lower in donors than in non-donors (2.8 v 4.1 events per 1000 person years; hazard ratio 0.66, 95% confidence interval 0.48 to 0.90). The risk of major cardiovascular events censored for death was no different in donors than in non-donors (1.7 v 2.0 events per 1000 person years; 0.85, 0.57 to 1.27). Results were similar in all sensitivity analyses. Older age and lower income were associated with a higher risk of death and major cardiovascular events in both donors and non-donors when each group was analysed separately. CONCLUSIONS: The risk of major cardiovascular events in donors is no higher in the first decade after kidney donation compared with a similarly healthy segment of the general population. While we will continue to follow people in this study, these interim results add to the evidence base supporting the safety of the practice among carefully selected donors.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.211

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.291
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it